diff --git a/_modules/arkouda/dataframe.html b/_modules/arkouda/dataframe.html index 22bf902ab6..0b785f6634 100644 --- a/_modules/arkouda/dataframe.html +++ b/_modules/arkouda/dataframe.html @@ -3020,6 +3020,69 @@
return pd.DataFrame(data=pandas_data)
return pd.Series(val.to_ndarray(), index=idx)
The set of category labels (determined automatically)
codes (pdarray, int64) – Category indices of each value
categories (Strings) – Unique category labels
categories (Strings) – Unique category labels
permutation (pdarray, int64) – The permutation that groups the values in the same order as categories
segments (pdarray, int64) – When values are grouped, the starting offset of each group
test (Union[Strings,Categorical]) – The values against which to test each value of ‘self`.
+test (Union[Strings,Categorical]) – The values against which to test each value of ‘self`.
The values self[in1d] are in the test Strings or Categorical object.
@@ -746,7 +746,7 @@numpy.bool
RegistrationError – Raised if there’s a server-side error or a mis-match of registered components
+RegistrationError – Raised if there’s a server-side error or a mis-match of registered components
TypeError – Raised if user_defined_name is not a str
RegistrationError – If the server was unable to register the Categorical with the user_defined_name
RegistrationError – If the server was unable to register the Categorical with the user_defined_name
RegistrationError – If the object is already unregistered or if there is a server error +
RegistrationError – If the object is already unregistered or if there is a server error when attempting to unregister
TypeError – if user_defined_name is not a string
RegistrationError – if there is an issue attempting to unregister any underlying components
RegistrationError – if there is an issue attempting to unregister any underlying components
TypeError – Raised if user_defined_name is not a str
RegistrationError – If the server was unable to register the BitVector with the user_defined_name
RegistrationError – If the server was unable to register the BitVector with the user_defined_name
values (pdarray or Strings) – The array of field values. If (u)int64, the values are used as-is for the +
values (pdarray or Strings) – The array of field values. If (u)int64, the values are used as-is for the binary representation of fields. If Strings, the values are converted to binary according to the mapping defined by the names and MSB_left arguments.
TypeError – Raised if user_defined_name is not a str
RegistrationError – If the server was unable to register the IPv4 with the user_defined_name
RegistrationError – If the server was unable to register the IPv4 with the user_defined_name
columns (List, tuple, pdarray, or Strings) – Column labels to use if the data does not include them. Elements must +
index (Index, pdarray, or Strings) – Index for the resulting frame. Defaults to an integer range.
columns (List, tuple, pdarray, or Strings) – Column labels to use if the data does not include them. Elements must be strings. Defaults to an stringified integer range.
RegistrationError – if user_defined_name is not registered
+RegistrationError – if user_defined_name is not registered
bool
RegistrationError – Raised if there’s a server-side error or a mismatch of registered components.
+RegistrationError – Raised if there’s a server-side error or a mismatch of registered components.
TypeError – Raised if user_defined_name is not a str.
RegistrationError – If the server was unable to register the DataFrame with the user_defined_name.
RegistrationError – If the server was unable to register the DataFrame with the user_defined_name.
Print DataFrame in Markdown-friendly format.
+mode (str, optional) – Mode in which file is opened, “wt” by default.
index (bool, optional, default True) – Add index (row) labels.
tablefmt (str = "grid") – Table format to call from tablulate: +https://pypi.org/project/tabulate/
storage_options (dict, optional) – Extra options that make sense for a particular storage connection, +e.g. host, port, username, password, etc., if using a URL that will be parsed by fsspec, +e.g., starting “s3://”, “gcs://”. +An error will be raised if providing this argument with a non-fsspec URL. +See the fsspec and backend storage implementation docs for the set +of allowed keys and values.
**kwargs – These parameters will be passed to tabulate.
Note
+This function should only be called on small DataFrames as it calls pandas.DataFrame.to_markdown: +https://pandas.pydata.org/pandas-docs/version/1.2.4/reference/api/pandas.DataFrame.to_markdown.html
+Examples
+>>> import arkouda as ak
+>>> ak.connect()
+>>> df = ak.DataFrame({"animal_1": ["elk", "pig"], "animal_2": ["dog", "quetzal"]})
+>>> print(df.to_markdown())
++----+------------+------------+
+| | animal_1 | animal_2 |
++====+============+============+
+| 0 | elk | dog |
++----+------------+------------+
+| 1 | pig | quetzal |
++----+------------+------------+
+
Suppress the index:
+>>> print(df.to_markdown(index = False))
++------------+------------+
+| animal_1 | animal_2 |
++============+============+
+| elk | dog |
++------------+------------+
+| pig | quetzal |
++------------+------------+
+
RegistrationError – If the object is already unregistered or if there is a server error +
RegistrationError – If the object is already unregistered or if there is a server error when attempting to unregister.
TypeError – If user_defined_name is not a string.
RegistrationError – If there is an issue attempting to unregister any underlying components.
RegistrationError – If there is an issue attempting to unregister any underlying components.
positions (bool, default=True) – Return tuple of boolean pdarrays that indicate positions in a and b of the intersection values.
unique (bool, default=False) – If the number of distinct values in a (and b) is equal to the size of @@ -4928,6 +4981,7 @@
DataFrame.tail()
DataFrame.to_csv()
DataFrame.to_hdf()
DataFrame.to_markdown()
DataFrame.to_pandas()
DataFrame.to_parquet()
DataFrame.transfer()
keys ((list of) pdarray, Strings, or Categorical) – The array to group by value, or if list, the column arrays to group by row
keys ((list of) pdarray, Strings, or Categorical) – The array to group by value, or if list, the column arrays to group by row
assume_sorted (bool) – If True, assume keys is already sorted (Default: False)
(list of) pdarray, Strings, or Categorical
+(list of) pdarray, Strings, or Categorical
RegistrationError – if user_defined_name is not registered
+RegistrationError – if user_defined_name is not registered
values (pdarray, Strings) – The values to put in each group’s segment
values (pdarray, Strings) – The values to put in each group’s segment
permute (bool) – If True (default), permute broadcast values back to the ordering of the original array on which GroupBy was called. If False, the broadcast values are grouped by value.
The broadcasted values
bool
RegistrationError – Raised if there’s a server-side error or a mismatch of registered components
+RegistrationError – Raised if there’s a server-side error or a mismatch of registered components
TypeError – Raised if user_defined_name is not a str
RegistrationError – If the server was unable to register the GroupBy with the user_defined_name
RegistrationError – If the server was unable to register the GroupBy with the user_defined_name
RegistrationError – If the object is already unregistered or if there is a server error +
RegistrationError – If the object is already unregistered or if there is a server error when attempting to unregister
TypeError – if user_defined_name is not a string
RegistrationError – if there is an issue attempting to unregister any underlying components
RegistrationError – if there is an issue attempting to unregister any underlying components
segments (pdarray, int64) – Offsets of the start of each row in the sparse matrix or grouped array. Must be sorted in ascending order.
values (pdarray, Strings) – The values to broadcast, one per row (or group)
values (pdarray, Strings) – The values to broadcast, one per row (or group)
size (int) – The total number of nonzeros in the matrix. If permutation is given, this argument is ignored and the size is inferred from the permutation array.
permutation (pdarray, int64) – The permutation to go from the original ordering of nonzeros to the ordering @@ -1582,7 +1582,7 @@
The broadcast values, one per nonzero
ValueError –
pda ((list of) pdarray, Strings, or Categorical) – Input array.
pda ((list of) pdarray, Strings, or Categorical) – Input array.
return_groups (bool, optional) – If True, also return grouping information for the array.
return_indices (bool, optional) – Only applicable if return_groups is True. If True, return unique key indices along with other groups
A DataFrame structure based on arkouda arrays.
Represents a date and/or time.
Represents a date and/or time.
Represents a date and/or time.
Represents an array of strings whose data resides on the
Represents an array of strings whose data resides on the
Represents an array of strings whose data resides on the
Represents an array of strings whose data resides on the
Represents a duration, the difference between two dates or times.
Represents a duration, the difference between two dates or times.
akabs
(→ arkouda.pdarrayclass.pdarray)
Return the element-wise absolute value of the array.
akcast
(→ Union[Union[arkouda.pdarrayclass.pdarray, ...)
akcast
(→ Union[Union[arkouda.pdarrayclass.pdarray, ...)
Cast an array to another dtype.
akcast
(→ Union[Union[arkouda.pdarrayclass.pdarray, ...)
akcast
(→ Union[Union[arkouda.pdarrayclass.pdarray, ...)
Cast an array to another dtype.
align
(*args)
bigint_from_uint_arrays
(arrays[, max_bits])
Create a bigint pdarray from an iterable of uint pdarrays.
broadcast
(segments, values[, size, permutation])
broadcast
(segments, values[, size, permutation])
Broadcast a dense column vector to the rows of a sparse matrix or grouped array.
broadcast
(segments, values[, size, permutation])
broadcast
(segments, values[, size, permutation])
Broadcast a dense column vector to the rows of a sparse matrix or grouped array.
broadcast
(segments, values[, size, permutation])
broadcast
(segments, values[, size, permutation])
Broadcast a dense column vector to the rows of a sparse matrix or grouped array.
broadcast_dims
(→ Tuple[int, Ellipsis])
cov
(→ numpy.float64)
Return the covariance of x and y
create_pdarray
(→ pdarray)
create_pdarray
(→ pdarray)
Return a pdarray instance pointing to an array created by the arkouda server.
create_pdarray
(→ pdarray)
create_pdarray
(→ pdarray)
Return a pdarray instance pointing to an array created by the arkouda server.
create_pdarray
(→ pdarray)
create_pdarray
(→ pdarray)
Return a pdarray instance pointing to an array created by the arkouda server.
ctz
(→ pdarray)
date_operators
(cls)
date_range
([start, end, periods, freq, tz, normalize, ...])
date_range
([start, end, periods, freq, tz, normalize, ...])
Creates a fixed frequency Datetime range. Alias for
date_range
([start, end, periods, freq, tz, normalize, ...])
date_range
([start, end, periods, freq, tz, normalize, ...])
Creates a fixed frequency Datetime range. Alias for
deg2rad
(→ arkouda.pdarrayclass.pdarray)
fmod
(→ pdarray)
Returns the element-wise remainder of division.
from_series
(→ Union[arkouda.pdarrayclass.pdarray, ...)
from_series
(→ Union[arkouda.pdarrayclass.pdarray, ...)
Converts a Pandas Series to an Arkouda pdarray or Strings object. If
from_series
(→ Union[arkouda.pdarrayclass.pdarray, ...)
from_series
(→ Union[arkouda.pdarrayclass.pdarray, ...)
Converts a Pandas Series to an Arkouda pdarray or Strings object. If
full
(→ Union[arkouda.pdarrayclass.pdarray, ...)
full
(→ Union[arkouda.pdarrayclass.pdarray, ...)
Create a pdarray filled with fill_value.
full
(→ Union[arkouda.pdarrayclass.pdarray, ...)
full
(→ Union[arkouda.pdarrayclass.pdarray, ...)
Create a pdarray filled with fill_value.
full_like
(→ arkouda.pdarrayclass.pdarray)
ip_address
(values)
Convert values to an Arkouda array of IP addresses.
isSupportedInt
(num)
isSupportedInt
(num)
isSupportedInt
(num)
isSupportedInt
(num)
isSupportedNumber
(num)
isinf
(→ arkouda.pdarrayclass.pdarray)
Return the element-wise isinf check applied to the array.
isnan
(→ arkouda.pdarrayclass.pdarray)
isnan
(→ arkouda.pdarrayclass.pdarray)
Return the element-wise isnan check applied to the array.
isnan
(→ arkouda.pdarrayclass.pdarray)
isnan
(→ arkouda.pdarrayclass.pdarray)
Return the element-wise isnan check applied to the array.
join_on_eq_with_dt
(...)
square
(→ arkouda.pdarrayclass.pdarray)
Return the element-wise square of the array.
standard_normal
(→ arkouda.pdarrayclass.pdarray)
standard_normal
(→ arkouda.pdarrayclass.pdarray)
Draw real numbers from the standard normal distribution.
standard_normal
(→ arkouda.pdarrayclass.pdarray)
standard_normal
(→ arkouda.pdarrayclass.pdarray)
Draw real numbers from the standard normal distribution.
std
(→ numpy.float64)
tanh
(→ arkouda.pdarrayclass.pdarray)
Return the element-wise hyperbolic tangent of the array.
timedelta_range
([start, end, periods, freq, name, closed])
timedelta_range
([start, end, periods, freq, name, closed])
Return a fixed frequency TimedeltaIndex, with day as the default
timedelta_range
([start, end, periods, freq, name, closed])
timedelta_range
([start, end, periods, freq, name, closed])
Return a fixed frequency TimedeltaIndex, with day as the default
to_csv
(columns, prefix_path[, names, col_delim, overwrite])
trunc
(→ arkouda.pdarrayclass.pdarray)
Return the element-wise truncation of the array.
uniform
(, high, seed, ...)
uniform
(, high, seed, ...)
Generate a pdarray with uniformly distributed random float values
uniform
(, high, seed, ...)
uniform
(, high, seed, ...)
Generate a pdarray with uniformly distributed random float values
union1d
(→ Union[arkouda.pdarrayclass.pdarray, ...)
The DType enum defines the supported Arkouda data types in string form.
TypeError – Raised if user_defined_name is not a str
RegistrationError – If the server was unable to register the BitVector with the user_defined_name
RegistrationError – If the server was unable to register the BitVector with the user_defined_name
codes (pdarray, int64) – Category indices of each value
categories (Strings) – Unique category labels
categories (Strings) – Unique category labels
permutation (pdarray, int64) – The permutation that groups the values in the same order as categories
segments (pdarray, int64) – When values are grouped, the starting offset of each group
test (Union[Strings,Categorical]) – The values against which to test each value of ‘self`.
+test (Union[Strings,Categorical]) – The values against which to test each value of ‘self`.
The values self[in1d] are in the test Strings or Categorical object.
@@ -2121,7 +2121,7 @@numpy.bool
RegistrationError – Raised if there’s a server-side error or a mis-match of registered components
+RegistrationError – Raised if there’s a server-side error or a mis-match of registered components
TypeError – Raised if user_defined_name is not a str
RegistrationError – If the server was unable to register the Categorical with the user_defined_name
RegistrationError – If the server was unable to register the Categorical with the user_defined_name
RegistrationError – If the object is already unregistered or if there is a server error +
RegistrationError – If the object is already unregistered or if there is a server error when attempting to unregister
TypeError – if user_defined_name is not a string
RegistrationError – if there is an issue attempting to unregister any underlying components
RegistrationError – if there is an issue attempting to unregister any underlying components
codes (pdarray, int64) – Category indices of each value
categories (Strings) – Unique category labels
categories (Strings) – Unique category labels
permutation (pdarray, int64) – The permutation that groups the values in the same order as categories
segments (pdarray, int64) – When values are grouped, the starting offset of each group
test (Union[Strings,Categorical]) – The values against which to test each value of ‘self`.
+test (Union[Strings,Categorical]) – The values against which to test each value of ‘self`.
The values self[in1d] are in the test Strings or Categorical object.
@@ -3086,7 +3086,7 @@numpy.bool
RegistrationError – Raised if there’s a server-side error or a mis-match of registered components
+RegistrationError – Raised if there’s a server-side error or a mis-match of registered components
TypeError – Raised if user_defined_name is not a str
RegistrationError – If the server was unable to register the Categorical with the user_defined_name
RegistrationError – If the server was unable to register the Categorical with the user_defined_name
RegistrationError – If the object is already unregistered or if there is a server error +
RegistrationError – If the object is already unregistered or if there is a server error when attempting to unregister
TypeError – if user_defined_name is not a string
RegistrationError – if there is an issue attempting to unregister any underlying components
RegistrationError – if there is an issue attempting to unregister any underlying components
codes (pdarray, int64) – Category indices of each value
categories (Strings) – Unique category labels
categories (Strings) – Unique category labels
permutation (pdarray, int64) – The permutation that groups the values in the same order as categories
segments (pdarray, int64) – When values are grouped, the starting offset of each group
test (Union[Strings,Categorical]) – The values against which to test each value of ‘self`.
+test (Union[Strings,Categorical]) – The values against which to test each value of ‘self`.
The values self[in1d] are in the test Strings or Categorical object.
@@ -4051,7 +4051,7 @@numpy.bool
RegistrationError – Raised if there’s a server-side error or a mis-match of registered components
+RegistrationError – Raised if there’s a server-side error or a mis-match of registered components
TypeError – Raised if user_defined_name is not a str
RegistrationError – If the server was unable to register the Categorical with the user_defined_name
RegistrationError – If the server was unable to register the Categorical with the user_defined_name
RegistrationError – If the object is already unregistered or if there is a server error +
RegistrationError – If the object is already unregistered or if there is a server error when attempting to unregister
TypeError – if user_defined_name is not a string
RegistrationError – if there is an issue attempting to unregister any underlying components
RegistrationError – if there is an issue attempting to unregister any underlying components
columns (List, tuple, pdarray, or Strings) – Column labels to use if the data does not include them. Elements must +
index (Index, pdarray, or Strings) – Index for the resulting frame. Defaults to an integer range.
columns (List, tuple, pdarray, or Strings) – Column labels to use if the data does not include them. Elements must be strings. Defaults to an stringified integer range.
RegistrationError – if user_defined_name is not registered
+RegistrationError – if user_defined_name is not registered
Notes
Generates the correlation matrix using Pearson R for all columns.
@@ -6495,12 +6495,12 @@bool
RegistrationError – Raised if there’s a server-side error or a mismatch of registered components.
+RegistrationError – Raised if there’s a server-side error or a mismatch of registered components.
See also
- +Notes
Objects registered with the server are immune to deletion until @@ -7307,13 +7307,13 @@
TypeError – Raised if user_defined_name is not a str.
RegistrationError – If the server was unable to register the DataFrame with the user_defined_name.
RegistrationError – If the server was unable to register the DataFrame with the user_defined_name.
See also
-unregister
, attach
, unregister_dataframe_by_name
, is_registered
unregister
, attach
, unregister_dataframe_by_name
, is_registered
Notes
Objects registered with the server are immune to deletion until @@ -8227,6 +8227,59 @@
Print DataFrame in Markdown-friendly format.
+mode (str, optional) – Mode in which file is opened, “wt” by default.
index (bool, optional, default True) – Add index (row) labels.
tablefmt (str = "grid") – Table format to call from tablulate: +https://pypi.org/project/tabulate/
storage_options (dict, optional) – Extra options that make sense for a particular storage connection, +e.g. host, port, username, password, etc., if using a URL that will be parsed by fsspec, +e.g., starting “s3://”, “gcs://”. +An error will be raised if providing this argument with a non-fsspec URL. +See the fsspec and backend storage implementation docs for the set +of allowed keys and values.
**kwargs – These parameters will be passed to tabulate.
Note
+This function should only be called on small DataFrames as it calls pandas.DataFrame.to_markdown: +https://pandas.pydata.org/pandas-docs/version/1.2.4/reference/api/pandas.DataFrame.to_markdown.html
+Examples
+>>> import arkouda as ak
+>>> ak.connect()
+>>> df = ak.DataFrame({"animal_1": ["elk", "pig"], "animal_2": ["dog", "quetzal"]})
+>>> print(df.to_markdown())
++----+------------+------------+
+| | animal_1 | animal_2 |
++====+============+============+
+| 0 | elk | dog |
++----+------------+------------+
+| 1 | pig | quetzal |
++----+------------+------------+
+
Suppress the index:
+>>> print(df.to_markdown(index = False))
++------------+------------+
+| animal_1 | animal_2 |
++============+============+
+| elk | dog |
++------------+------------+
+| pig | quetzal |
++------------+------------+
+
RegistrationError – If the object is already unregistered or if there is a server error +
RegistrationError – If the object is already unregistered or if there is a server error when attempting to unregister.
See also
-register
, attach
, unregister_dataframe_by_name
, is_registered
register
, attach
, unregister_dataframe_by_name
, is_registered
Notes
Objects registered with the server are immune to deletion until @@ -8454,7 +8507,7 @@
TypeError – If user_defined_name is not a string.
RegistrationError – If there is an issue attempting to unregister any underlying components.
RegistrationError – If there is an issue attempting to unregister any underlying components.
columns (List, tuple, pdarray, or Strings) – Column labels to use if the data does not include them. Elements must +
index (Index, pdarray, or Strings) – Index for the resulting frame. Defaults to an integer range.
columns (List, tuple, pdarray, or Strings) – Column labels to use if the data does not include them. Elements must be strings. Defaults to an stringified integer range.
RegistrationError – if user_defined_name is not registered
+RegistrationError – if user_defined_name is not registered
Notes
Generates the correlation matrix using Pearson R for all columns.
@@ -10492,12 +10545,12 @@bool
RegistrationError – Raised if there’s a server-side error or a mismatch of registered components.
+RegistrationError – Raised if there’s a server-side error or a mismatch of registered components.
See also
- +Notes
Objects registered with the server are immune to deletion until @@ -11304,13 +11357,13 @@
TypeError – Raised if user_defined_name is not a str.
RegistrationError – If the server was unable to register the DataFrame with the user_defined_name.
RegistrationError – If the server was unable to register the DataFrame with the user_defined_name.
See also
-unregister
, attach
, unregister_dataframe_by_name
, is_registered
unregister
, attach
, unregister_dataframe_by_name
, is_registered
Notes
Objects registered with the server are immune to deletion until @@ -12226,7 +12279,60 @@
Print DataFrame in Markdown-friendly format.
+mode (str, optional) – Mode in which file is opened, “wt” by default.
index (bool, optional, default True) – Add index (row) labels.
tablefmt (str = "grid") – Table format to call from tablulate: +https://pypi.org/project/tabulate/
storage_options (dict, optional) – Extra options that make sense for a particular storage connection, +e.g. host, port, username, password, etc., if using a URL that will be parsed by fsspec, +e.g., starting “s3://”, “gcs://”. +An error will be raised if providing this argument with a non-fsspec URL. +See the fsspec and backend storage implementation docs for the set +of allowed keys and values.
**kwargs – These parameters will be passed to tabulate.
Note
+This function should only be called on small DataFrames as it calls pandas.DataFrame.to_markdown: +https://pandas.pydata.org/pandas-docs/version/1.2.4/reference/api/pandas.DataFrame.to_markdown.html
+Examples
+>>> import arkouda as ak
+>>> ak.connect()
+>>> df = ak.DataFrame({"animal_1": ["elk", "pig"], "animal_2": ["dog", "quetzal"]})
+>>> print(df.to_markdown())
++----+------------+------------+
+| | animal_1 | animal_2 |
++====+============+============+
+| 0 | elk | dog |
++----+------------+------------+
+| 1 | pig | quetzal |
++----+------------+------------+
+
Suppress the index:
+>>> print(df.to_markdown(index = False))
++------------+------------+
+| animal_1 | animal_2 |
++============+============+
+| elk | dog |
++------------+------------+
+| pig | quetzal |
++------------+------------+
+
Send this DataFrame to a pandas DataFrame.
Save DataFrame to disk as parquet, preserving column names.
Sends a DataFrame to a different Arkouda server.
Unregister this DataFrame object in the arkouda server which was previously registered using register() and/or attached to using attach().
RegistrationError – If the object is already unregistered or if there is a server error +
RegistrationError – If the object is already unregistered or if there is a server error when attempting to unregister.
See also
-register
, attach
, unregister_dataframe_by_name
, is_registered
register
, attach
, unregister_dataframe_by_name
, is_registered
Notes
Objects registered with the server are immune to deletion until @@ -12440,8 +12546,8 @@
Function to unregister DataFrame object by name which was registered with the arkouda server via register().
TypeError – If user_defined_name is not a string.
RegistrationError – If there is an issue attempting to unregister any underlying components.
RegistrationError – If there is an issue attempting to unregister any underlying components.
Overwrite the dataset with the name provided with this dataframe. If the dataset does not exist it is added.
Computes the number of rows on the arkouda server and updates the size parameter.
numpy.bool
RegistrationError – Raised if there’s a server-side error or a mis-match of registered components
+RegistrationError – Raised if there’s a server-side error or a mis-match of registered components
Notes
Objects registered with the server are immune to deletion until @@ -12784,12 +12890,12 @@
TypeError – Raised if user_defined_name is not a str
RegistrationError – If the server was unable to register the Datetimes with the user_defined_name
RegistrationError – If the server was unable to register the Datetimes with the user_defined_name
RegistrationError – If the object is already unregistered or if there is a server error +
RegistrationError – If the object is already unregistered or if there is a server error when attempting to unregister
Notes
Objects registered with the server are immune to deletion until @@ -12842,8 +12948,8 @@
Bases: _AbstractBaseTime
Represents a date and/or time.
Datetime is the Arkouda analog to pandas DatetimeIndex and @@ -12873,139 +12979,139 @@
The .values
attribute is always in nanoseconds with int64 dtype.
Return True iff the object is contained in the registry or is a component of a registered object.
@@ -13018,12 +13124,12 @@Attributes
numpy.bool
- Raises:
-RegistrationError – Raised if there’s a server-side error or a mis-match of registered components
+RegistrationError – Raised if there’s a server-side error or a mis-match of registered components
Notes
Objects registered with the server are immune to deletion until @@ -13031,13 +13137,13 @@
Attributes -
- -isocalendar()[source]#
+- +isocalendar()[source]#
-
- -register(user_defined_name)[source]#
+- +register(user_defined_name)[source]#
Register this Datetime object and underlying components with the Arkouda server
@@ -13070,14 +13176,14 @@
- Parameters:
@@ -13051,12 +13157,12 @@AttributesReturn type: -
- +
- Raises:
- -
TypeError – Raised if user_defined_name is not a str
- +
RegistrationError – If the server was unable to register the Datetimes with the user_defined_name
RegistrationError – If the server was unable to register the Datetimes with the user_defined_name
Attributes -
- -sum()[source]#
+- +sum()[source]#
Return the sum of all elements in the array.
-
- -to_pandas()[source]#
+- +to_pandas()[source]#
Convert array to a pandas DatetimeIndex. Note: if the array size exceeds client.maxTransferBytes, a RuntimeError is raised.
@@ -13087,19 +13193,19 @@Attributes -
- -unregister()[source]#
+- +unregister()[source]#
Unregister this Datetime object in the arkouda server which was previously registered using register() and/or attached to using attach()
- Raises:
-RegistrationError – If the object is already unregistered or if there is a server error +
RegistrationError – If the object is already unregistered or if there is a server error when attempting to unregister
Notes
Objects registered with the server are immune to deletion until @@ -13109,8 +13215,8 @@
Attributes -
- -class arkouda.Datetime(pda, unit: str = _BASE_UNIT)[source]#
+- +class arkouda.Datetime(pda, unit: str = _BASE_UNIT)[source]#
Bases:
_AbstractBaseTime
Represents a date and/or time.
Datetime is the Arkouda analog to pandas DatetimeIndex and @@ -13140,139 +13246,139 @@
AttributesNotes
The
-.values
attribute is always in nanoseconds with int64 dtype.-
- -- -property date#
-+ -
+ + +
+
- +is_registered() numpy.bool_ [source]#
Return True iff the object is contained in the registry or is a component of a registered object.
@@ -13285,12 +13391,12 @@Attributes
numpy.bool
- Raises:
-RegistrationError – Raised if there’s a server-side error or a mis-match of registered components
+RegistrationError – Raised if there’s a server-side error or a mis-match of registered components
Notes
Objects registered with the server are immune to deletion until @@ -13298,13 +13404,13 @@
Attributes -
- -isocalendar()[source]#
+- +isocalendar()[source]#
-
- -register(user_defined_name)[source]#
+- +register(user_defined_name)[source]#
Register this Datetime object and underlying components with the Arkouda server
@@ -13337,14 +13443,14 @@
- Parameters:
@@ -13318,12 +13424,12 @@AttributesReturn type: -
- +
- Raises:
- -
TypeError – Raised if user_defined_name is not a str
- +
RegistrationError – If the server was unable to register the Datetimes with the user_defined_name
RegistrationError – If the server was unable to register the Datetimes with the user_defined_name
Attributes -
- -sum()[source]#
+- +sum()[source]#
Return the sum of all elements in the array.
-
- -to_pandas()[source]#
+- +to_pandas()[source]#
Convert array to a pandas DatetimeIndex. Note: if the array size exceeds client.maxTransferBytes, a RuntimeError is raised.
@@ -13354,19 +13460,19 @@Attributes -
- -unregister()[source]#
+- +unregister()[source]#
Unregister this Datetime object in the arkouda server which was previously registered using register() and/or attached to using attach()
- Raises:
-RegistrationError – If the object is already unregistered or if there is a server error +
RegistrationError – If the object is already unregistered or if there is a server error when attempting to unregister
Notes
Objects registered with the server are immune to deletion until @@ -13441,7 +13547,7 @@
Attributes
- Parameters:
-
values (pdarray or Strings) – The array of field values. If (u)int64, the values are used as-is for the +
- @@ -13578,7 +13684,7 @@
values (pdarray or Strings) – The array of field values. If (u)int64, the values are used as-is for the binary representation of fields. If Strings, the values are converted to binary according to the mapping defined by the names and MSB_left arguments.
Attributes
See also
- +Examples
>>> rng = ak.random.default_rng() @@ -13663,7 +13769,7 @@Attributes
- Parameters:
- @@ -13707,7 +13813,7 @@
-
- +
keys ((list of) pdarray, Strings, or Categorical) – The array to group by value, or if list, the column arrays to group by row
keys ((list of) pdarray, Strings, or Categorical) – The array to group by value, or if list, the column arrays to group by row
assume_sorted (bool) – If True, assume keys is already sorted (Default: False)
Attributes
- Type:
-- @@ -14089,7 +14195,7 @@
(list of) pdarray, Strings, or Categorical
+(list of) pdarray, Strings, or Categorical
Attributes
- Raises:
-RegistrationError – if user_defined_name is not registered
+RegistrationError – if user_defined_name is not registered
@@ -14105,7 +14211,7 @@Attributes
- Parameters:
-
- +
values (pdarray, Strings) – The values to put in each group’s segment
values (pdarray, Strings) – The values to put in each group’s segment
- @@ -14115,7 +14221,7 @@
permute (bool) – If True (default), permute broadcast values back to the ordering of the original array on which GroupBy was called. If False, the broadcast values are grouped by value.
Attributes
The broadcasted values
- Return type:
-- +
- Raises:
@@ -14245,7 +14351,7 @@
Attributes
bool
- Raises:
-RegistrationError – Raised if there’s a server-side error or a mismatch of registered components
+RegistrationError – Raised if there’s a server-side error or a mismatch of registered components
@@ -14580,7 +14686,7 @@AttributesRaises:
- @@ -14594,8 +14700,8 @@
- -
TypeError – Raised if user_defined_name is not a str
- +
RegistrationError – If the server was unable to register the GroupBy with the user_defined_name
RegistrationError – If the server was unable to register the GroupBy with the user_defined_name
Attributes -
- -size() Tuple[groupable, arkouda.pdarrayclass.pdarray] [source]#
+- +size() Tuple[groupable, arkouda.pdarrayclass.pdarray] [source]#
Count the number of elements in each group, i.e. the number of times each key appears. This counts the total number of rows (including NaN values).
@@ -14785,7 +14891,7 @@
@@ -14810,7 +14916,7 @@Attributes
- Raises:
-RegistrationError – If the object is already unregistered or if there is a server error +
RegistrationError – If the object is already unregistered or if there is a server error when attempting to unregister
AttributesRaises:
- @@ -14883,21 +14989,21 @@
- -
TypeError – if user_defined_name is not a string
- +
RegistrationError – if there is an issue attempting to unregister any underlying components
RegistrationError – if there is an issue attempting to unregister any underlying components
Attributes -
- -class arkouda.GroupBy(keys: groupable | None = None, assume_sorted: bool = False, dropna: bool = True, **kwargs)[source]#
+- +class arkouda.GroupBy(keys: groupable | None = None, assume_sorted: bool = False, dropna: bool = True, **kwargs)[source]#
Group an array or list of arrays by value, usually in preparation for aggregating the within-group values of another array.
- Parameters:
-
- +
keys ((list of) pdarray, Strings, or Categorical) – The array to group by value, or if list, the column arrays to group by row
keys ((list of) pdarray, Strings, or Categorical) – The array to group by value, or if list, the column arrays to group by row
assume_sorted (bool) – If True, assume keys is already sorted (Default: False)
-
- -nkeys#
+- +nkeys#
The number of key arrays (columns)
- Type:
@@ -14907,8 +15013,8 @@Attributes -
- -size[source]#
+- +size[source]#
The length of the input array(s), i.e. number of rows
- Type:
@@ -14918,8 +15024,8 @@Attributes -
- -permutation#
+- +permutation#
The permutation that sorts the keys array(s) by value (row)
- Type:
@@ -14929,19 +15035,19 @@Attributes -
- -unique_keys#
+- +unique_keys#
The unique values of the keys array(s), in grouped order
- Type:
-(list of) pdarray, Strings, or Categorical
+(list of) pdarray, Strings, or Categorical
-
- -ngroups#
+- +ngroups#
The length of the unique_keys array(s), i.e. number of groups
- Type:
@@ -14951,8 +15057,8 @@Attributes -
- -segments#
+- +segments#
The start index of each group in the grouped array(s)
- Type:
@@ -14962,8 +15068,8 @@Attributes -
- -logger#
+- +logger#
Used for all logging operations
- Type:
@@ -14973,8 +15079,8 @@Attributes -
- -dropna#
+- +dropna#
If True, and the groupby keys contain NaN values, the NaN values together with the corresponding row will be dropped. Otherwise, the rows corresponding to NaN values will be kept.
@@ -15006,18 +15112,18 @@Attributes -
- -Reductions#
+- +Reductions#
-
- -AND(values: arkouda.pdarrayclass.pdarray) Tuple[arkouda.pdarrayclass.pdarray | List[arkouda.pdarrayclass.pdarray | arkouda.strings.Strings], arkouda.pdarrayclass.pdarray] [source]#
+- +AND(values: arkouda.pdarrayclass.pdarray) Tuple[arkouda.pdarrayclass.pdarray | List[arkouda.pdarrayclass.pdarray | arkouda.strings.Strings], arkouda.pdarrayclass.pdarray] [source]#
Bitwise AND of values in each segment.
Using the permutation stored in the GroupBy instance, group another array of values and perform a bitwise AND reduction on @@ -15046,8 +15152,8 @@
Attributes -
- -OR(values: arkouda.pdarrayclass.pdarray) Tuple[arkouda.pdarrayclass.pdarray | List[arkouda.pdarrayclass.pdarray | arkouda.strings.Strings], arkouda.pdarrayclass.pdarray] [source]#
+- +OR(values: arkouda.pdarrayclass.pdarray) Tuple[arkouda.pdarrayclass.pdarray | List[arkouda.pdarrayclass.pdarray | arkouda.strings.Strings], arkouda.pdarrayclass.pdarray] [source]#
Bitwise OR of values in each segment.
Using the permutation stored in the GroupBy instance, group another array of values and perform a bitwise OR reduction on @@ -15076,8 +15182,8 @@
Attributes -
- -XOR(values: arkouda.pdarrayclass.pdarray) Tuple[arkouda.pdarrayclass.pdarray | List[arkouda.pdarrayclass.pdarray | arkouda.strings.Strings], arkouda.pdarrayclass.pdarray] [source]#
+- +XOR(values: arkouda.pdarrayclass.pdarray) Tuple[arkouda.pdarrayclass.pdarray | List[arkouda.pdarrayclass.pdarray | arkouda.strings.Strings], arkouda.pdarrayclass.pdarray] [source]#
Bitwise XOR of values in each segment.
Using the permutation stored in the GroupBy instance, group another array of values and perform a bitwise XOR reduction on @@ -15106,8 +15212,8 @@
Attributes -
- -aggregate(values: groupable, operator: str, skipna: bool = True, ddof: arkouda.dtypes.int_scalars = 1) Tuple[groupable, groupable] [source]#
+- +aggregate(values: groupable, operator: str, skipna: bool = True, ddof: arkouda.dtypes.int_scalars = 1) Tuple[groupable, groupable] [source]#
Using the permutation stored in the GroupBy instance, group another array of values and apply a reduction to each group’s values.
@@ -15154,8 +15260,8 @@
Attributes -
- -all(values: arkouda.pdarrayclass.pdarray) Tuple[arkouda.pdarrayclass.pdarray | List[arkouda.pdarrayclass.pdarray | arkouda.strings.Strings], arkouda.pdarrayclass.pdarray] [source]#
+- +all(values: arkouda.pdarrayclass.pdarray) Tuple[arkouda.pdarrayclass.pdarray | List[arkouda.pdarrayclass.pdarray | arkouda.strings.Strings], arkouda.pdarrayclass.pdarray] [source]#
Using the permutation stored in the GroupBy instance, group another array of values and perform an “and” reduction on each group.
@@ -15183,8 +15289,8 @@Attributes -
- -any(values: arkouda.pdarrayclass.pdarray) Tuple[arkouda.pdarrayclass.pdarray | List[arkouda.pdarrayclass.pdarray | arkouda.strings.Strings], arkouda.pdarrayclass.pdarray] [source]#
+- +any(values: arkouda.pdarrayclass.pdarray) Tuple[arkouda.pdarrayclass.pdarray | List[arkouda.pdarrayclass.pdarray | arkouda.strings.Strings], arkouda.pdarrayclass.pdarray] [source]#
Using the permutation stored in the GroupBy instance, group another array of values and perform an “or” reduction on each group.
@@ -15210,8 +15316,8 @@
Attributes -
- -argmax(values: arkouda.pdarrayclass.pdarray) Tuple[groupable, arkouda.pdarrayclass.pdarray] [source]#
+- +argmax(values: arkouda.pdarrayclass.pdarray) Tuple[groupable, arkouda.pdarrayclass.pdarray] [source]#
Using the permutation stored in the GroupBy instance, group another array of values and return the location of the first maximum of each group’s values.
@@ -15255,8 +15361,8 @@Attributes -
- -argmin(values: arkouda.pdarrayclass.pdarray) Tuple[groupable, arkouda.pdarrayclass.pdarray] [source]#
+- +argmin(values: arkouda.pdarrayclass.pdarray) Tuple[groupable, arkouda.pdarrayclass.pdarray] [source]#
Using the permutation stored in the GroupBy instance, group another array of values and return the location of the first minimum of each group’s values.
@@ -15301,8 +15407,8 @@Attributes -
- -static attach(user_defined_name: str) GroupBy [source]#
+- +static attach(user_defined_name: str) GroupBy [source]#
Function to return a GroupBy object attached to the registered name in the arkouda server which was registered using register()
- Raises:
-RegistrationError – if user_defined_name is not registered
+RegistrationError – if user_defined_name is not registered
@@ -15326,13 +15432,13 @@Attributes -
- -broadcast(values: arkouda.pdarrayclass.pdarray | arkouda.strings.Strings, permute: bool = True) arkouda.pdarrayclass.pdarray | arkouda.strings.Strings [source]#
+- +broadcast(values: arkouda.pdarrayclass.pdarray | arkouda.strings.Strings, permute: bool = True) arkouda.pdarrayclass.pdarray | arkouda.strings.Strings [source]#
Fill each group’s segment with a constant value.
- Parameters:
-
- +
values (pdarray, Strings) – The values to put in each group’s segment
values (pdarray, Strings) – The values to put in each group’s segment
- @@ -15342,7 +15448,7 @@
permute (bool) – If True (default), permute broadcast values back to the ordering of the original array on which GroupBy was called. If False, the broadcast values are grouped by value.
Attributes
The broadcasted values
- Return type:
-- +
- Raises:
@@ -15383,8 +15489,8 @@
Attributes -
- -static build_from_components(user_defined_name: str = None, **kwargs) GroupBy [source]#
+- +static build_from_components(user_defined_name: str = None, **kwargs) GroupBy [source]#
function to build a new GroupBy object from component keys and permutation.
- Parameters:
@@ -15403,8 +15509,8 @@Attributes -
- -count() Tuple[groupable, arkouda.pdarrayclass.pdarray] [source]#
+- +count() Tuple[groupable, arkouda.pdarrayclass.pdarray] [source]#
Count the number of elements in each group, i.e. the number of times each key appears. This counts the total number of rows (including NaN values).
@@ -15436,8 +15542,8 @@
Attributes -
- -first(values: groupable_element_type) Tuple[groupable, groupable_element_type] [source]#
+- +first(values: groupable_element_type) Tuple[groupable, groupable_element_type] [source]#
First value in each group.
- Parameters:
@@ -15454,13 +15560,13 @@Attributes -
- -static from_return_msg(